Image segmentation involves partitioning a digital image into two or more sets of pixels (or other image elements). For example a label may be assigned to each image element so that image elements with the same label share at least some visual characteristics and image elements with different labels differ with respect to those visual characteristics. In this way a foreground of an image may be separated from a background for example, or objects and boundaries may be located. Image segmentation is a difficult and complex problem and there is a need to improve the quality and speed of image segmentation systems.
Examples of applications in which image segmentation is used are medical imaging, locating objects in satellite images, face recognition, fingerprint recognition, machine vision and many others.
Interactive segmentation in which a user imposes certain constraints for segmentation by specifying certain image elements that are either part of an object of interest or part of the background has become popular in different domains as it can reduce the ambiguity of segmentation caused by complex object appearance. However, user interaction can often be cumbersome requiring many interactions and repeated brush strokes in order to segment an image. User guided image segmentation may also be effortful and time consuming for the user and is often difficult to carry out by novice users.
There is a need to provide interactive image segmentation that will segment an image with greater speed and less user interaction than current systems. For example, to power assist a human user in cutting out a desired object from an image in a robust manner.
The embodiments described below are not limited to implementations which solve any or all of the disadvantages of known image segmentation systems.